The invention relates to an image processor and a color printing apparatus to which the image processor is applied, the image processor having the function of binary-coding color half-tone image data so that the image data can be outputted to apparatuses not having a pixel-based tone control system.
In the case of outputting full color image data to printing apparatuses and displays which do not provide tone control on a pixel basis, a binary-coding process is necessary to reduce the tone of the color components of a pixel to two levels: the dot present level and the dot absent level.
An example of printing original image data will be considered using a printing apparatus that can output dots only in two tone levels per color component. The original image data consists of three color components, cyan (C), magenta (M), yellow (Y), which are the primary colors of inks. Each of the color components belonging to a pixel can take a total of 256 tone levels from 0 to 255. In such a case, the C, M, Y dots must be binary-coded for each pixel of the image data to determine that such dots are to be printed (ON) or not (OFF).
Various binary-coding techniques are available. A minimum average error method and an error diffusion method are in wide use and are excellent techniques in terms of resolution and tone reproducibility. The minimum average error method corrects the data value of a pixel to be binary-coded based on a weighted mean value of a quantization error caused in already binary-coded pixels adjacent the pixel to be binary-coded. The error diffusion method adds a quantization error caused at the time of binary-coding a pixel to neighboring pixels that have not yet been binary-coded by diffusion. What makes the former different from the latter is the timing at which the error diffusion process is executed; the two techniques are completely equivalent logically. The error diffusion method is disclosed in "R. Floyd et al., 1975 SID International Symposium Digest of Technical papers, 4.3, pp. 36 (1975) and also in Japanese Patent Unexamined Publication No. 284173/1989 ("IMAGE PROCESSOR AND APPARATUS"). On the other hand, the minimum average error method is disclosed in "J. F. Jarvice, C. N. Judice and W. H. Ninke; Computer Graphics and Image Processing, Vol. 5, No. 1, pp. 13 (1976)".
To apply the minimum average error method or the error diffusion method to the binary-coding of a color image, the error diffusion is performed on a color component basis independently. For example, the process of binary-coding the color component C is performed independently of the color components M and Y. Therefore, whether the C dot is superposed on the M dot or the Y dot on a single pixel is random, which means that no control is provided to make the dot easy or difficult to be superposed, or the like.
A problem arises when gray data that is achromatic is binary-coded. In the case of a printing apparatus having only the primary color inks C, M, Y, a black dot is usually produced by superposing the three color dots one upon another on a single pixel. However, as described above, the ordinary adaptive algorithm for spatial grayscale for color images performs the error diffusing process on each color component independently. Thus, how dots are superposed cannot be completely controlled. In binary-coding achromatic gray data of an intermediate density, the three color dots are superposed at random. That is, besides a dot produced by superposing the three colors C, M, Y, an output including a dot produced by superposing two colors out of the three, a single color dot, and a pixel without color ink also may be present. For example, if gray data in which the tone level of an original image is 128/255 for each of the three color components C, M, Y is binary-coded, the probability that each color component dot will be binary-coded to ON is almost 1/2. As shown in the following table, total of eight combinations of colors are produced after the pixel-based binary coding process at an almost equal probability of 1/8.
______________________________________ C Dot M Dot Y Dot Color ______________________________________ (1) ON ON ON BLACK (2) ON ON OFF BLUE (3) ON OFF ON GREEN (4) ON OFF OFF CYAN (5) OFF ON ON RED (6) OFF ON OFF MAGENTA (7) OFF OFF ON YELLOW (8) OFF OFF OFF WHITE ______________________________________
Even if the original image data is achromatic gray, the binary-coded results thereof are a set of pixels whose colors are different. Hence, to adjust such a mixture of different colors so as to be achromatic is quite difficult. Although each of the eight combinations is likely to appear at an equal probability, such probabilities may be disturbed by variations, so that a predetermined combination may appear at a larger ratio than that of another combination, and this causes inconsistency in produced colors. The human eye perceives even slight variations in gray balance. Once a portion that should be gray is colored to be non-achromatic, the mismatching is so overemphasized to the human eye that it perceives a significant deterioration in image quality.
In the case of a printer capable of using black ink (K) besides the three color inks, C, M, Y, a black pixel for case (1) in which all the three color dots C, M, Y are binary-coded to ON can be replaced by a pixel consisting only of K ink (C, M, Y are OFF and only K is ON). This contributes to improving the density and gray balance of the black dots, but the problem that the data consists of pixels of different colors cannot be eliminated. Consequently, the problem of unmatched gray balance is left unsolved.
To obtain stable reproduction of an achromatic area, an under color removal (UCR) technique has been proposed. The UCR technique is designed to remove the black component K from the C, M, Y components before binary-coding. In this case, tone level data of the four color components C', M', Y', and K are generated by the UCR process based on the original image tone data of C, M, Y components, and the color components C', M', Y', K are binary-coded thereafter. The simplest example of the UCR process is as follows.
K=MIN (C, M, Y) PA1 C'=C-K PA1 Y'=Y-K PA1 (1) an increase in the number of binary-coding process steps is minimized; and PA1 (2) the processing can be initiated without waiting for all the color component data to be available.
The C', M', Y', K components are generated by the above algorithm, where MIN (C, M, Y) is the function for finding a minimum of the C, M, Y components.
Then, the C', M', Y', K values obtained by the UCR process are binary-coded by error diffusion method or the like to generate binary-coded dots of the respective color components C, M, Y, K. In the case of using the K ink, the binary-coded results of C', M', Y', K may be printed as they are, whereas in the case of using only the three color inks C, M, Y, then the K dot is replaced by the superposition of the three colors C, M, Y.
If the original image data is achromatic, the values of C, M, Y are equal to one another. Thus, after the UCR process, all of the C', M', Y' components become zero, leaving only the K component. Therefore, the binary-coded results indicate that only the K dot exists. This means that the achromatic area consists only of black dots, thereby avoiding generation of gray balance unmatching and inconsistency in the produced color due to the gray area being made up of pixels of various colors.
However, this technique involves not only the additional UCR process, but also the binary-coding operation for the K component in addition to the C, M, Y components. Therefore, the scale of the binary-coding operation increases by 4/3, which is a problem. Since the binary-coding operation of the error diffusion method or the like includes a number of process steps and is complicated, any increase in processing time and processing hardware such as a memory is considered a substantial problem.
These are the problems encountered by the conventional adaptive algorithm for spatial grayscale. To summarize, whether the C dot is superposed on the M dot or the Y dot on a single pixel is random, which means that no control is provided to make the dot easy or difficult to be superposed, or the like.
In contrast, a technique for increasing the probability that the respective color dots will be superposed using the error diffusion method has been proposed in Japanese Patent Unexamined Publication No. 6948/1992 ("METHOD OF BINARY-CODING COLOR IMAGE"). The object thereof is to allow binary-coded color image data to be compressed at a high compression ratio. Therefore, a binary-coding technique is provided which is capable of making pixels of the respective colors easy to be superposed. A summary of the concept this technique is as follows.
Binary-coded color component signals of a target pixel are sorted in descending order and binary-coded as sorted. If the binary-coded results of the already binary-coded color components are OFF, then the color components thereafter in descending order are forced to be OFF, making sure that they cannot be ON. According to such technique, small color signal components cannot be ON unless larger color signal components are ON, making the ON dots easy to be superposed.
However, this technique involves the operation of sorting the respective color data of a target pixel in descending order. That is, the binary-coding process cannot be started unless all the color data of the target pixel are ready, which is a problem. Thus, even if the image data per color is to be received on a line basis or on a screen basis, the binary-coding process cannot be started from receipt of the color component, making it necessary for the received color components to be stored until all the color data are ready. From this arises the problem of reduced processing speed and a requirement for larger storage. The object of the above-mentioned publication No. 6948/1992 is only to improve the data compression ratio, and the specification provides no method for controlling gray balance.